settings_suggest Cloud-Native Orchestration

Kubernetes & Helm

Kubernetes consulting and Helm engineering by dedicated engineers who work with AI tools. AI drafts Helm charts, manifests and GitOps config and speeds up incident and log triage, while your engineer reviews and tests every change - so production-grade clusters are ready sooner.

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auto_awesome Why Kubernetes?

Managing Complexity at Scale

Kubernetes (K8s) is the industry standard for automating deployment, scaling, and management of containerized applications. It provides the framework to run distributed systems resiliently, taking care of scaling and failover for your application.

At PixoBots, our K8s architects build production-ready clusters, author custom Helm charts for reusable deployments, and implement GitOps workflows using ArgoCD or Flux. We keep your infrastructure declarative, versioned and designed for high availability.

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Auto-scaling
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Rolling Updates
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Self-healing
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Declarative Config
Kubernetes cluster management

Orchestration

Cloud Native

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What We Offer in Kubernetes

Delivering production-grade orchestration for your distributed applications.

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dns

Cluster Provisioning

Setup and management of managed K8s (EKS, GKE, AKS) or bare-metal clusters with high availability.

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sailing

Helm Chart Authoring

Creating custom, versioned Helm charts to package and deploy complex applications consistently.

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sync_alt

GitOps Workflows

Implementing ArgoCD or Flux for declarative, Git-driven deployments with automatic drift detection.

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Network Policies & RBAC

Hardening cluster security with fine-grained Role-Based Access Control and strict network isolation policies.

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grain

Service Mesh (Istio/Linkerd)

Implementing service meshes for advanced traffic management, observability, and mutual TLS encryption.

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visibility

Monitoring & Logging

Full-stack observability setup with Prometheus, Grafana, and ELK stack integrated into your K8s environment.

Technical Advantage

Why Orchestrate with PixoBots?

Build a resilient, self-healing infrastructure that grows with your business.

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Cloud Agnostic

Run your K8s workloads on any cloud provider or on-premise without vendor lock-in.

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Resource Optimization

Efficient bin-packing ensures you get the most out of your compute resources.

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Self Healing

Automatic restarts and rescheduling of failed containers keep services available through failures.

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Secrets Management

Securely manage sensitive data with K8s Secrets or Vault integration.

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AI-Augmented Engineers

Your dedicated engineer uses AI tools to draft charts, policies and runbooks and to triage cluster events faster, and reviews every change before it is applied.

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Low-Risk Releases

Canary or Blue/Green deployments with native K8s primitives, so new versions roll out gradually and can be rolled back quickly.

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Beyond Go-Live: Running the Cluster

Creating a cluster is the easy part. Most Kubernetes effort goes into keeping it current, safe and recoverable.

Upgrades as routine work

Kubernetes ships a new minor release roughly every four months, and managed providers retire old versions on a fixed calendar. We check manifests and Helm charts for deprecated APIs before each upgrade, rehearse it on a non-production cluster, and use PodDisruptionBudgets and surge node pools so workloads move off old nodes gradually.

Traffic, certificates and guardrails

We route traffic with Gateway API or a maintained ingress controller, automate TLS certificates with cert-manager, and enforce rules with policy engines such as Kyverno or OPA Gatekeeper - for example blocking privileged pods or images from untrusted registries. If you still depend on the retired community ingress-nginx controller, we plan the move to a supported alternative.

Backup and recovery

Etcd snapshots protect the control plane on self-managed clusters, and tools such as Velero back up namespaces and persistent volumes. Because the rest of the configuration lives in Git through GitOps, rebuilding a cluster becomes a repeatable, rehearsed procedure rather than an improvised one.

Pixel & Bots

Pixel-perfect software, delivered at AI speed

PixoBots stands for Pixel & Bots. Our Bots are dedicated developers who work with AI tools: AI takes the repetitive work, a developer reviews every line, and the result is pixel-perfect.

Pixel

Polished UI and clean, tested code - detail is part of the job, not an afterthought.

Bots

Dedicated developers who join your team and use AI for boilerplate, tests and documentation.

Savings

AI-assisted delivery can save more than 50% of development cost compared with traditional development.

How AI-augmented delivery works

Ready to Master Your Container Fleet?

Ship with confidence at any scale with our Kubernetes and Helm experts. Let's build your cloud-native future today.

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help_outline FAQ

Frequently asked questions

Do we actually need Kubernetes? expand_more
You need Kubernetes when you run many containerized services that must scale automatically, recover from failures and release with little or no downtime. For a single application or a small team, a managed container service or Docker Compose is often simpler and cheaper. We assess your workload first and recommend Kubernetes only when its operational overhead pays off.
Should we use managed Kubernetes like EKS, AKS or GKE, or run our own cluster? expand_more
Most teams should use a managed service such as Amazon EKS, Azure AKS or Google GKE, because the cloud provider runs the control plane, upgrades and much of the security patching. Self-managed or bare-metal clusters make sense for on-premises requirements, data residency or very specific hardware needs.
How long does it take to migrate our applications to Kubernetes? expand_more
A first production-ready cluster with one or two migrated services typically takes a few weeks, while a full migration of a larger platform can take several months. Timelines depend on how many services you have, whether they are already containerized, stateful components such as databases, and your CI/CD and security requirements.
How do you keep Kubernetes clusters secure? expand_more
We apply role-based access control with least privilege, network policies to limit traffic between services, pod security standards, image scanning and signed images, and encrypted secrets managed with Kubernetes Secrets or Vault. Clusters are kept on supported Kubernetes versions, since each minor release receives patches for only around a year.
How can we control Kubernetes costs? expand_more
Kubernetes costs are controlled mainly by right-sizing workloads. We set realistic CPU and memory requests and limits, enable cluster and pod autoscaling, use spot or preemptible nodes for suitable workloads, remove idle environments, and add cost monitoring per namespace or team so spending is visible and owned.
Can we run databases and other stateful workloads on Kubernetes? expand_more
It is possible, using StatefulSets, persistent volumes and database operators such as CloudNativePG for PostgreSQL. For most teams, though, a managed database service from the cloud provider is simpler and safer, because backups, failover and patching are handled for you. We usually keep production databases outside the cluster unless there is a clear reason, such as on-premises hosting or portability across environments.